sampSurf-class: Class "sampSurf"
In sampSurf: Sampling Surface Simulation for Areal Sampling Methods

Description Objects from the Class Slots Methods Author(s) References See Also Examples

This class allows one to collect a population of "Stem" (actually subclasses thereof) objects along with their inclusion zones for a given sampling method or protocol and generate the sampling surface resulting from the method. One can think of the sampling surface grid as generating all possible samples of size one over the population based on the grid cell size. That is, the number of sample point locations is equivalent to the number of grid cells. At each grid cell, an estimate based on one sample is recorded. Because inclusion zones will often overlap, the estimate at the individual grid cells will be a function of those logs whose inclusion zones overlapped the grid cell center. In this way, the surface is constructed representing the samples at each point. One can think of the surface as a discrete approximation to the actual continuous surface—the approximation getting better as the grid cell size goes to zero (grid resolution increases).

Much of this is explained in far more detail in the references below. One can also generate multiple copies based on different log populations and average those surfaces to get a result that minimizes any possible irregularities in a particular sample draw of “Stem” objects. This has not been built into the package yet, but is simple enough to do, and can be added later.

Note that only one attribute (e.g., volume, surface area, etc.) can be represented for a given sampling surface. However, it is trivial to use the same population of logs and inclusion zones to estimate a surface for a different attribute on the same tract. It is also straightforward to use the same population of logs and base tract extents to compare different sampling methods or protocols.

Objects can be created by calls of the form new("sampSurf", ...). However, this is not recommended because the objects are fairly complex. Instead, one can use the object constructor sampSurf to create new objects. There is more than than one form of the function, so please refer to its methods for alternatives. More details are found in "The sampSurf Class" vignette.

description:: Object of class "character": a character description to be associated with this surface.
izContainer:: Object of class "izContainer": A collection or population of down log or standing tree "InclusionZone" objects.
tract:: Object of class "Tract": This is the tract over which to generate the sampling surface, and on which the objects in the izContainer slot exist.
estimate:: Object of class "character": The attribute estimate name for the sampling surface represented on this tract; i.e., "volume", or number of stems ("Density"), etc., per unit area.
surfStats:: Object of class "list": A list object with the summary statistics for the sampling surface with estimate attribute in the estimate slot.

bbox: signature(obj = "sampSurf"): Retrieve the bounding box matrix.
hist: signature(x = "sampSurf"): Histogram of the sampling distribution.
perimeter: signature(object = "sampSurf"): Graphical perimeter of the surface.
plot3D: signature(x = "sampSurf"): Display the surface in 3D with rgl.
plot: signature(x = "sampSurf", y = "missing"): Plot the surface.
show: signature(object = "sampSurf"): raster-like description of the surface grid.
summary: signature(object = "sampSurf"): Detailed summary of the surface statistics.

Jeffrey H. Gove

: Williams, M. S. 2001. New approach to areal sampling in ecological surveys. Forest Ecology and Management 154:11–22.

: Williams, M. S. 2001. Nonuniform random sampling: an alternative method of variance reduction for forest surveys. Canadian Journal of Forest Research 31: 2080–2088.